BOL: All site news

Primer BLAST !

BioStar — Tue, 28 Apr 2020 00:28:49 -0500

BLAST team added a new feature (Max 3' match), shown in Figure 1, to Primer-BLAST that limits the length of 3' exon matches when designing exon-exon spanning primers. This makes it less likely that primers specifically designed to amplify transcripts will also amplify genomic DNA contamination in expression assays. See the NCBI Insights post (https://go.usa.gov/xvUT4) for more details.

If you have any questions or concerns, please contact blast-help@ncbi.nlm.nih.gov

SAMHAR-COVID19 Hackathon

BioStar — Fri, 17 Apr 2020 06:47:10 -0500

Centre for Development of Advanced Computing (C-DAC) under the aegis of the National Supercomputing Mission (NSM), a Ministry of Electronics & Information Technology (MeitY) and Department of Science & Technology (DST) initiative, in association with NVIDIA & OpenACC, announces the SAMHAR-COVID19 Hackathon.

Pandemic outbreak such as Coronavirus outbreak can create huge challenges for the Government and Public Health Officials to gather information quickly and coordinate a response. In such a situation, Artificial Intelligence (AI) can play a huge role in predicting, minimizing and stalling its spread of the virus.

C-DAC has embarked on a program SAMHAR-COVID19 (Supercomputing using AI, ML, Healthcare Analytics based Research for combating COVID19). This opportunity will provide researchers to find solutions for Identifying, Tracking and Forecasting outbreaks of COVID19 and Facilitating Drug Discovery as well.

Participants can update submissions multiple times till the Registration End date.
Each entry can be submitted by a Team comprising of minimum 3 and maximum 5 members (Including the Team Lead).
Participants will have to share the complete work activities with C-DAC. And C-DAC will have right to use the submitted application/solution for SAMHAR-COVID19 programs.
The Award will be given to the Selected/Winning Entry irrespective of the number of members in the Team (members may choose to distribute the amount among themselves).
The decision of the Eminent Jury on the I3 Award will be final and binding.
Award can be for the Team/Company/Institution, as submitted in the Application and cannot be changed later.
Submissions will be considered void if they are in whole or part ill-eligible, incomplete, damaged, altered, counterfeit, obtained through fraud or late submission.

More at https://samhar-covid19hackathon.cdac.in/

Submit your SARS-CoV-2 sequence data to GenBank

Neel — Thu, 09 Apr 2020 18:28:25 -0500

Submit your SARS-CoV-2 sequence data to GenBank and SRA with our new submission landing page. Submission is simple and streamlined *and* there’s a rapid turnaround. https://submit.ncbi.nlm.nih.gov/sarscov2/

Quickly and easily add your SARS-CoV-2 sequence data to the growing public archive with new, special features and support from NCBI. new SARS-CoV-2 sequence submission landing page will help you get started. GenBank submissions are accessioned and released in approximately 1-2 working days, and Sequence Read Archive (SRA) submissions typically processed and released within hours. Submission is simple!

More information is available on NCBI Insights. https://ncbiinsights.ncbi.nlm.nih.gov/2020/04/09/sars-cov2-data-streamlined-submission-rapid-turnaround/

China’s BGI says it can sequence a genome for just $100

Neel — Sat, 29 Feb 2020 04:49:43 -0600

Using technology originally acquired in the US, the Chinese gene giant BGI Group says it will make genome sequencing cheaper than ever, breaking the $100 barrier for the first time.

The Shenzhen company says the low cost will be possible with an “extreme” DNA sequencing system it plans to offer that is capable of decoding the genomes of 100,000 people a year.

Ref: https://www.technologyreview.com/s/615289/china-bgi-100-dollar-genome/

Rasa's New Service Completed For Molecular Docking Map Atom Service

RASA Life Sciences — Sun, 23 Feb 2020 23:29:48 -0600

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Curated set of ribosomal RNA (rRNA) reference sequences (targeted loci) with verifiable organism

Rahul Nayak — Sun, 23 Feb 2020 02:17:30 -0600

MCBI have a curated set of ribosomal RNA (rRNA) reference sequences (targeted loci) with verifiable organism sources and current names. This set is critical for correctly identifying and classifying prokaryotic (bacteria and archaea) and fungal samples. To provide easy access to these sequences, we recently added a separate rRNA/ITS databases section on the nucleotide BLAST page for these targeted sequences that makes it convenient to quickly identify source organisms. The new databases are:

*16S ribosomal RNA (Bacteria and Archaea)

*18S ribosomal RNA sequences (SSU) from Fungi type and reference material

*28S ribosomal RNA sequences (LSU) from Fungi type and reference material

*Internal transcribed spacer region (ITS) from Fungi type and reference material

You can also download these from the BLAST db FTP area. See the NCBI Insights post for more detail.

Useful links

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BLAST form with rRNA/ITS databases

BLAST db download

Targeted loci

If you have any questions or concerns, please contact blast-help@ncbi.nlm.nih.gov

Complete genome sequence of Wuhan seafood market pneumonia virus is out !

Jit — Fri, 31 Jan 2020 02:36:59 -0600

Wuhan-Hu-1 claimed at least 40 lives and infected at least 1300 others in China. Cases are now being reported from Thailand, Singapore, Malaysia, South Korea, Japan, Vietnam, Nepal, France, Australia and even as far as the US. On Jan 10 2020, while news of the first fatality was barely trickling in, the 29,903 letters constituting the viral genome from an affected individual in Wuhan had already been elucidated (even though a few corrections were made subsequently). All the viral genome sequences from affected individuals are very very close to each other. Several are identical and none has more than 5 differences (99.983% similarity). This strongly suggests that transmission into humans came from a single pointed source and happened very recently, between Sep-Dec 2019.

Check out the detail at https://www.ncbi.nlm.nih.gov/nuccore/MN908947

IgBLAST: a popular NCBI package for classifying and analyzing immunoglobulin (IG) and T cell receptor (TCR) variable domain sequences

BioJoker — Thu, 23 Jan 2020 11:34:37 -0600

NCBI team released a new version of IgBLAST with four new improvements. IgBLAST is a popular NCBI package for classifying and analyzing immunoglobulin (IG) and T cell receptor (TCR) variable domain sequences. Improvements are:

1. Support for the new FWR4 annotation feature in the AIRR format, both in standard format and in the AIRR alignment format.

2. The previous “-penalty” parameter was renamed as -V_penalty to be consistent with other IgBLAST penalty options.

3. Restored constant internal BLAST search parameters for domain annotation (i.e., FWR/CDR) such that this process is not influenced by user parameters.

4. Corrected FWR/CDR annotations for certain mouse VK and rat VH germline genes.

IgBLAST 1.15.0 is available for download from the BLAST FTP area. See the the new manual on GitHub for information about setting up and running IgBLAST.

If you have any questions or concerns, please contact blast-help@ncbi.nlm.nih.gov

New Layout for BLAST ftp Database Site

Jit — Tue, 21 Jan 2020 11:57:11 -0600

As announced previously, the new default database version for BLAST+ is dbV5. To complete this transition, the ftp database site will be updated to support this change. We expect this change to happen around February 4^th, please adjust your scripts or procedures accordingly.

Here is a list of what is changing:

All databases at the root level will be dbV5.
The dbV5 file naming, “_v5” will be removed. Databases with no “_vX” descriptor will be dbV5.
dbV4 tarballs will be renamed with "_v4", files included in tarball will not be renamed.
dbV4 databases will be moved to a v4 subdirectory.
As of 1/13/20 the Cloud directory will be frozen with no more new entries.
The will be no more updates to dbV4 databases.
The FASTA directory will contain nr, nt, swissprot, and pdbaa files.

If you have any questions or concerns, please contact blast-help@ncbi.nlm.nih.gov

Artificial intelligence is more accurate than doctors in diagnosing breast cancer

BioStar — Wed, 01 Jan 2020 22:12:34 -0600

Artificial intelligence is more accurate than doctors in diagnosing breast cancer from mammograms, a study in the journal Nature suggests.

An international team, including researchers from Google Health and Imperial College London, designed and trained a computer model on X-ray images from nearly 29,000 women.

The algorithm outperformed six radiologists in reading mammograms.

AI was still as good as two doctors working together.

Unlike humans, AI is tireless. Experts say it could improve detection. Read More: https://www.bbc.com/news/health-50857759